It is possible for everyone to improve their cardiorespiratory fitness through effective planning of activities. Exercise sessions must be performed frequently enough, and the sessions should regularly include both easier exercise sessions as well as more demanding sessions. In general, sessions should have variation both in their intensity and their duration, and this creates a “training load”, a measure of how much the body's homeostasis has been disturbed with training. In addition to changes in daily training load, weekly and seasonal training must include variation. The variation in training load is needed to continue fitness development while avoiding injuries or developing overtraining symptoms.
Monitoring of training load, recovery, and fitness level development is important to ensure that athletes train at an optimal level towards their goal and avoid overloading. Appropriate load and fitness monitoring aids in determining whether an athlete is adapting to a training program and is minimizing the risk of overtraining, developing illness, and/or injury.
To be able to make decisions on future training a user needs to know the current trajectory of their training, referred to as their training status. At certain points in a user's training, they may wish to decrease or increase training in specific ways to elicit a specific reaction, such as peaking for an important race. This requires not only information on each individual exercise, but information on a plurality of exercises to determine the cumulative effect they have had on a user's fitness.
Currently it is not possible to get information on training status based on data from multiple exercises. At first sight that kind of application seems to need a lot of resources. Embedded systems, such as heart rate monitors, fitness devices, mobile phones, PDA devices, tablet computers, or wrist top computers have quite limited CPU and memory resources to be used by any utility application. Those resources are only a fraction of that of an ordinary PC. This is a challenge for an implementation of any physiological method.
Polar V800 with Polar web service (Polar Electric Oy, Finland) presents a system recording training data and giving Training Status from limited group of alternatives. There are physiological conditions which are not identified or that would be very unreliable. Such technically challenging conditions are “Unproductive”, “Overreaching”, “Productive” or “Peaking”.
There are other prior art generally relating to determining a readiness of a user. Document US2016/0023047 (U.S. Pat. No. 9,622,685 B2) presents a system for providing training load schedule for peak performance using earphones with biometric sensors. Document US 2016/0220866 presents a device helping a user to plan the proper timing for setting a next training session.